Instructions to use cortexso/tinyllama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use cortexso/tinyllama with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="cortexso/tinyllama", filename="tinyllama-1.1b-chat-v1.0-q2_k.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use cortexso/tinyllama with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: llama-cli -hf cortexso/tinyllama:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: llama-cli -hf cortexso/tinyllama:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf cortexso/tinyllama:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf cortexso/tinyllama:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf cortexso/tinyllama:Q4_K_M
Use Docker
docker model run hf.co/cortexso/tinyllama:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use cortexso/tinyllama with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cortexso/tinyllama" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cortexso/tinyllama", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cortexso/tinyllama:Q4_K_M
- Ollama
How to use cortexso/tinyllama with Ollama:
ollama run hf.co/cortexso/tinyllama:Q4_K_M
- Unsloth Studio new
How to use cortexso/tinyllama with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for cortexso/tinyllama to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for cortexso/tinyllama to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cortexso/tinyllama to start chatting
- Docker Model Runner
How to use cortexso/tinyllama with Docker Model Runner:
docker model run hf.co/cortexso/tinyllama:Q4_K_M
- Lemonade
How to use cortexso/tinyllama with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull cortexso/tinyllama:Q4_K_M
Run and chat with the model
lemonade run user.tinyllama-Q4_K_M
List all available models
lemonade list
| license: apache-2.0 | |
| pipeline_tag: text-generation | |
| tags: | |
| - cortex.cpp | |
| ## Overview | |
| The [TinyLlama](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) project aims to pretrain a 1.1B Llama model on 3 trillion tokens. This is the chat model finetuned on a diverse range of synthetic dialogues generated by ChatGPT. | |
| ## Variants | |
| | No | Variant | Cortex CLI command | | |
| | --- | --- | --- | | |
| | 1 | [TinyLLama-1b](https://huggingface.co/cortexso/tinyllama/tree/1b) | `cortex run tinyllama:1b` | | |
| ## Use it with Jan (UI) | |
| 1. Install **Jan** using [Quickstart](https://jan.ai/docs/quickstart) | |
| 2. Use in Jan model Hub: | |
| ```bash | |
| cortexhub/tinyllama | |
| ``` | |
| ## Use it with Cortex (CLI) | |
| 1. Install **Cortex** using [Quickstart](https://cortex.jan.ai/docs/quickstart) | |
| 2. Run the model with command: | |
| ```bash | |
| cortex run tinyllama | |
| ``` | |
| ## Credits | |
| - **Author:** Microsoft | |
| - **Converter:** [Homebrew](https://www.homebrew.ltd/) | |
| - **Original License:** [License](https://choosealicense.com/licenses/apache-2.0/) | |
| - **Papers:** [Tinyllama Paper](https://arxiv.org/abs/2401.02385) |